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MySQL 8 for Big Data

You're reading from   MySQL 8 for Big Data Effective data processing with MySQL 8, Hadoop, NoSQL APIs, and other Big Data tools

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Product type Paperback
Published in Oct 2017
Publisher Packt
ISBN-13 9781788397186
Length 296 pages
Edition 1st Edition
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Authors (4):
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Chintan Mehta Chintan Mehta
Author Profile Icon Chintan Mehta
Chintan Mehta
Shabbir Challawala Shabbir Challawala
Author Profile Icon Shabbir Challawala
Shabbir Challawala
Jaydip Lakhatariya Jaydip Lakhatariya
Author Profile Icon Jaydip Lakhatariya
Jaydip Lakhatariya
Kandarp Patel Kandarp Patel
Author Profile Icon Kandarp Patel
Kandarp Patel
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Toc

Table of Contents (11) Chapters Close

Preface 1. Introduction to Big Data and MySQL 8 FREE CHAPTER 2. Data Query Techniques in MySQL 8 3. Indexing your data for High-Performing Queries 4. Using Memcached with MySQL 8 5. Partitioning High Volume Data 6. Replication for building highly available solutions 7. MySQL 8 Best Practices 8. NoSQL API for Integrating with Big Data Solutions 9. Case study: Part I - Apache Sqoop for exchanging data between MySQL and Hadoop 10. Case study: Part II - Real time event processing using MySQL applier

Using of Memcached

Memcached can be used at various stages in real-world applications. Its integration with MySQL makes it more comfortable for you to handle Big Data. Let's see the importance of using Memcached by understanding the different advantages.

Performance tuner

We always care about the performance while handing Big Data. We may have many questions before we start, such as how MySQL can be optimized from a performance perspective. We assume that managing Big Data with MySQL can impact performance as this is a pure structured database. But no! MySQL has a pretty simple way to handle Big Data by integrating Memcached and using it as a NoSQL database. This way, it will improve the performance latency and provide...

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